# encoding: utf-8 # @Time : 2024/3/3 # @Author : Spike # @Descr : import json import os import time import logging from toolbox import get_conf, update_ui, log_chat from toolbox import ChatBotWithCookies import requests class MoonShotInit: def __init__(self): self.llm_model = None self.url = 'https://api.moonshot.cn/v1/chat/completions' self.api_key = get_conf('MOONSHOT_API_KEY') def __converter_file(self, user_input: str): what_ask = [] for f in user_input.splitlines(): if os.path.exists(f): files = [] if os.path.isdir(f): file_list = os.listdir(f) files.extend([os.path.join(f, file) for file in file_list]) else: files.append(f) for file in files: if file.split('.')[-1] in ['pdf']: with open(file, 'r') as fp: from crazy_functions.crazy_utils import read_and_clean_pdf_text file_content, _ = read_and_clean_pdf_text(fp) what_ask.append({"role": "system", "content": file_content}) return what_ask def __converter_user(self, user_input: str): what_i_ask_now = {"role": "user", "content": user_input} return what_i_ask_now def __conversation_history(self, history): conversation_cnt = len(history) // 2 messages = [] if conversation_cnt: for index in range(0, 2 * conversation_cnt, 2): what_i_have_asked = { "role": "user", "content": str(history[index]) } what_gpt_answer = { "role": "assistant", "content": str(history[index + 1]) } if what_i_have_asked["content"] != "": if what_gpt_answer["content"] == "": continue messages.append(what_i_have_asked) messages.append(what_gpt_answer) else: messages[-1]['content'] = what_gpt_answer['content'] return messages def _analysis_content(self, chuck): chunk_decoded = chuck.decode("utf-8") chunk_json = {} content = "" try: chunk_json = json.loads(chunk_decoded[6:]) content = chunk_json['choices'][0]["delta"].get("content", "") except: pass return chunk_decoded, chunk_json, content def generate_payload(self, inputs, llm_kwargs, history, system_prompt, stream): self.llm_model = llm_kwargs['llm_model'] llm_kwargs.update({'use-key': self.api_key}) messages = [] if system_prompt: messages.append({"role": "system", "content": system_prompt}) messages.extend(self.__converter_file(inputs)) for i in history[0::2]: # 历史文件继续上传 messages.extend(self.__converter_file(i)) messages.extend(self.__conversation_history(history)) messages.append(self.__converter_user(inputs)) header = { "Content-Type": "application/json", "Authorization": f"Bearer {self.api_key}", } payload = { "model": self.llm_model, "messages": messages, "temperature": llm_kwargs.get('temperature', 0.3), # 1.0, "top_p": llm_kwargs.get('top_p', 1.0), # 1.0, "n": llm_kwargs.get('n_choices', 1), "stream": stream } return payload, header def generate_messages(self, inputs, llm_kwargs, history, system_prompt, stream): payload, headers = self.generate_payload(inputs, llm_kwargs, history, system_prompt, stream) response = requests.post(self.url, headers=headers, json=payload, stream=stream) chunk_content = "" gpt_bro_result = "" for chuck in response.iter_lines(): chunk_decoded, check_json, content = self._analysis_content(chuck) chunk_content += chunk_decoded if content: gpt_bro_result += content yield content, gpt_bro_result, '' else: error_msg = msg_handle_error(llm_kwargs, chunk_decoded) if error_msg: yield error_msg, gpt_bro_result, error_msg break def msg_handle_error(llm_kwargs, chunk_decoded): use_ket = llm_kwargs.get('use-key', '') api_key_encryption = use_ket[:8] + '****' + use_ket[-5:] openai_website = f' 请登录OpenAI查看详情 https://platform.openai.com/signup api-key: `{api_key_encryption}`' error_msg = '' if "does not exist" in chunk_decoded: error_msg = f"[Local Message] Model {llm_kwargs['llm_model']} does not exist. 模型不存在, 或者您没有获得体验资格." elif "Incorrect API key" in chunk_decoded: error_msg = f"[Local Message] Incorrect API key. OpenAI以提供了不正确的API_KEY为由, 拒绝服务." + openai_website elif "exceeded your current quota" in chunk_decoded: error_msg = "[Local Message] You exceeded your current quota. OpenAI以账户额度不足为由, 拒绝服务." + openai_website elif "account is not active" in chunk_decoded: error_msg = "[Local Message] Your account is not active. OpenAI以账户失效为由, 拒绝服务." + openai_website elif "associated with a deactivated account" in chunk_decoded: error_msg = "[Local Message] You are associated with a deactivated account. OpenAI以账户失效为由, 拒绝服务." + openai_website elif "API key has been deactivated" in chunk_decoded: error_msg = "[Local Message] API key has been deactivated. OpenAI以账户失效为由, 拒绝服务." + openai_website elif "bad forward key" in chunk_decoded: error_msg = "[Local Message] Bad forward key. API2D账户额度不足." elif "Not enough point" in chunk_decoded: error_msg = "[Local Message] Not enough point. API2D账户点数不足." elif 'error' in str(chunk_decoded).lower(): try: error_msg = json.dumps(json.loads(chunk_decoded[:6]), indent=4, ensure_ascii=False) except: error_msg = chunk_decoded return error_msg def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWithCookies, history:list=[], system_prompt:str='', stream:bool=True, additional_fn:str=None): chatbot.append([inputs, ""]) if additional_fn is not None: from core_functional import handle_core_functionality inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot) yield from update_ui(chatbot=chatbot, history=history, msg="等待响应") # 刷新界面 gpt_bro_init = MoonShotInit() history.extend([inputs, '']) stream_response = gpt_bro_init.generate_messages(inputs, llm_kwargs, history, system_prompt, stream) for content, gpt_bro_result, error_bro_meg in stream_response: chatbot[-1] = [inputs, gpt_bro_result] history[-1] = gpt_bro_result yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 if error_bro_meg: chatbot[-1] = [inputs, error_bro_meg] history = history[:-2] yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 break log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=gpt_bro_result) def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_slience=False): gpt_bro_init = MoonShotInit() watch_dog_patience = 60 # 看门狗的耐心, 设置10秒即可 stream_response = gpt_bro_init.generate_messages(inputs, llm_kwargs, history, sys_prompt, True) moonshot_bro_result = '' for content, moonshot_bro_result, error_bro_meg in stream_response: moonshot_bro_result = moonshot_bro_result if error_bro_meg: if len(observe_window) >= 3: observe_window[2] = error_bro_meg return f'{moonshot_bro_result} 对话错误' # 观测窗 if len(observe_window) >= 1: observe_window[0] = moonshot_bro_result if len(observe_window) >= 2: if (time.time() - observe_window[1]) > watch_dog_patience: observe_window[2] = "请求超时，程序终止。" raise RuntimeError(f"{moonshot_bro_result} 程序终止。") return moonshot_bro_result if __name__ == '__main__': moon_ai = MoonShotInit() for g in moon_ai.generate_messages('hello', {'llm_model': 'moonshot-v1-8k'}, [], '', True): print(g)